Defining efficient enzyme–cofactor pairs for bioorthogonal profiling of protein methylation
Bibliographic record
Abstract
Protein methyltransferase (PMT)-mediated posttranslational modification of histone and nonhistone substrates modulates stability, localization, and interacting partners of target proteins in diverse cellular contexts. These events play critical roles in normal biological processes and are frequently deregulated in human diseases. In the course of identifying substrates of individual PMTs, bioorthogonal profiling of protein methylation (BPPM) has demonstrated its merits. In this approach, specific PMTs are engineered to process S-adenosyl-L-methionine (SAM) analogs as cofactor surrogates and label their substrates with distinct chemical modifications for target elucidation. Despite the proof-of-concept advancement of BPPM, few efforts have been made to explore its generality. With two cancer-relevant PMTs, EuHMT1 (GLP1/KMT1D) and EuHMT2 (G9a/KMT1C), as models, we defined the key structural features of engineered PMTs and matched SAM analogs that can render the orthogonal enzyme-cofactor pairs for efficient catalysis. Here we have demonstrated that the presence of sulfonium-β-sp(2) carbon and flexible, medium-sized sulfonium-δ-substituents are crucial for SAM analogs as BPPM reagents. The bulky cofactors can be accommodated by tailoring the conserved Y1211/Y1154 residues and nearby hydrophobic cavities of EuHMT1/2. Profiling proteome-wide substrates with BPPM allowed identification of >500 targets of EuHMT1/2 with representative targets validated using native EuHMT1/2 and SAM. This finding indicates that EuHMT1/2 may regulate many cellular events previously unrecognized to be modulated by methylation. The present work, therefore, paves the way to a broader application of the BPPM technology to profile methylomes of diverse PMTs and elucidate their downstream functions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".